Building TrustworthyDigital Twins for Patient-Centred Medicine
Università degli Studi di Salerno
The University of Salerno (UNISA) is a public, multidisciplinary university located in Campania, southern Italy. Ideally linked to the historical legacy of the Schola Medica Salernitana, one of Europe’s earliest medical institutions, UNISA has developed into a modern campus university with its main campus in Fisciano and a health sciences campus in Baronissi. The university hosts a large academic community of around 40,000 students and offers teaching, research and third-mission activities across medicine, engineering, computer science, natural sciences, humanities, social sciences, law and economics. In the biomedical area, UNISA combines clinical, translational and computational expertise, with particular strengths in pathology, medical imaging, laboratory medicine, clinical data interpretation and AI-enabled health research. Through TWIN-X, UNISA contributes its experience in clinical validation, oncology, cardiology, digital pathology and multimodal biomedical data integration.
Role within TWIN-X
UNISA leads Work Package 6, “Clinical demonstrators and validation”, which is responsible for translating the TWIN-X technical framework into clinically meaningful oncology and cardiology demonstrators. UNISA coordinates the definition of demonstrator protocols, case-selection rules, datasets, endpoints and trust criteria, ensuring that validation activities are aligned with the multimodal digital twin framework, explainability requirements and clinical use-case priorities. UNISA also contributes to the harmonisation of clinical narratives, pathology information, laboratory data, medication data and timeline representations, supporting the creation of structured, interpretable patient-level information for downstream modelling. In the imaging and pathology workstreams, UNISA helps align slide metadata, labels and clinical annotations with common project schemas. During validation, UNISA will support cohort preparation, annotation workflows, radiology and pathology checks, generalisation assessment, calibration analyses and clinical interpretation of results. Overall, UNISA acts as a clinical and methodological bridge between data generation, AI development, and real-world validation.
